Call for Papers - AI in Smart Grids
The modern power system faces great challenges and opportunities from increasing penetration of renewables, digitalization, hybrid operation of AC and DC grids, and aging infrastructure. Artificial Intelligence (AI) has seen fast evolution and growth in recent years to modernize systems. AI-based methods have advanced a wide range of techniques and approaches that can be employed to solve complex power system problems (e.g. load forecasting, planning, operation, as well as transient stability and control). On the other hand, the concept of “smart grid” emerged to take advantage of information and communication technologies in the modern power system, in order to provide for increasing the penetration of renewable energy by deploying the advanced metering infrastructure and smart appliances. This has raised many new problems in modern power system, which may not be suitable to analytical treatment, and need to be solved using learning algorithms within the field of AI.
The main goal of this Special Issue is to pay special attention to AI based applications on modern power system research and bring researchers, scientists, engineers together on a common platform to demonstrate novel ideas on use of AI in this field.
The relevant topics include:
AI architecture and trends used in power systemsMachine learning algorithms in smart grids Blockchain integrated AI based solutions in electrical power system applicationsBatteries based solution with AIArtificial intelligence applied to power system optimizationOptimized management in microgrids and energy hubsAI-driven solutions for the next generation of the smart-gridDecentralization and digitalization in smart gridsData analytics for electrical energy systems.
All proposed papers must be submitted via https://www.editorialmanager.com/elen/Default.aspx by selecting “SI – AI for smart grids”.
Author Guidelines, which is available at: https://www.springer.com/journal/202/submission-guidelines
Full manuscript due: 15 November 2020
Decision notification: 1 February 2021
Prof. Ahmet Onen, Abdullah Gul University, email@example.com
Prof. Shiping Wen, University of Technology Sydney), Shiping.Wen@uts.edu.au
Dr. Taha Selim Ustun, Fukushima Renewable Energy Institute, firstname.lastname@example.org
Prof. Zhiwei Liu, HuazhongUniversity of Science and Technology, email@example.com